Abstract：Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy's lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.
葛建军, 李春霞. 一种基于信息熵的雷达动态自适应选择跟踪方法[J]. 雷达学报, 2017, 6(6): 587-593.
Ge Jianjun, Li Chunxia. A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy. JOURNAL OF RADARS, 2017, 6(6): 587-593.
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